ODSC - Open Data Science

APRIL 28, 2023

As critical data flows across an organization from various business applications, data silos become a big issue. The data silos, missing data, and errors make data management tedious and time-consuming, and they’re barriers to ensuring the accuracy and consistency of your data before it is usable by AI/ML.

ML 98

ML ML Data Silos Data Quality 98

AWS Machine Learning Blog

JANUARY 13, 2023

Analyzing real-world healthcare and life sciences (HCLS) data poses several practical challenges, such as distributed data silos, lack of sufficient data at any single site for rare events, regulatory guidelines that prohibit data sharing, infrastructure requirement, and cost incurred in creating a centralized data repository.

AWS 105

AWS Analytics Analytics Machine Learning 105

AWS Machine Learning Blog

MARCH 15, 2024

Additionally, locally trained information can expose private data if reconstructed through an inference attack. To mitigate these risks, the FL model uses personalized training algorithms and effective masking and parameterization before sharing information with the training coordinator. In such scenarios, you can use FedML Octopus.

AWS 140

AWS ML ML Machine Learning 140

Becoming Human

MARCH 16, 2023

AI began back in the 1950s as a simple series of “if, then rules” and made its way into healthcare two decades later after more complex algorithms were developed. Machine Learning Machine learning (ML) focuses on training computer algorithms to learn from data and improve their performance, without being explicitly programmed.

AI 139

AI AI Deep Learning Deep Learning 139

DrivenData Labs

MARCH 30, 2023

Techniques used include homomorphic encryption and/or secure multiparty computation (SMPC) protocols such as secure aggregation and private set intersection. Working collaboratively, these two labs have made remarkable strides in developing federated learning algorithms and systems for real-world applications.

Machine Learning 162

Machine Learning Machine Learning Data Science Algorithm 162

AWS Machine Learning Blog

JANUARY 13, 2023

Analyzing real-world healthcare and life sciences (HCLS) data poses several practical challenges, such as distributed data silos, lack of sufficient data at a single site for rare events, regulatory guidelines that prohibit data sharing, infrastructure requirement, and cost incurred in creating a centralized data repository.

AWS 101

AWS Analytics Analytics Machine Learning 101

Pickl AI

DECEMBER 4, 2023

So, what is Data Intelligence with an example? For example, an e-commerce company uses Data Intelligence to analyze customer behavior on their website. Through advanced analytics and Machine Learning algorithms, they identify patterns such as popular products, peak shopping times, and customer preferences.

Data Analysis 52

Data Analysis Data Analysis Artificial Intelligence Artificial Intelligence 52